Submission¶
Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace
In [1]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px
init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [2]:
#load data
df = px.data.gapminder()
df.head()
Out[2]:
| country | continent | year | lifeExp | pop | gdpPercap | iso_alpha | iso_num | |
|---|---|---|---|---|---|---|---|---|
| 0 | Afghanistan | Asia | 1952 | 28.801 | 8425333 | 779.445314 | AFG | 4 |
| 1 | Afghanistan | Asia | 1957 | 30.332 | 9240934 | 820.853030 | AFG | 4 |
| 2 | Afghanistan | Asia | 1962 | 31.997 | 10267083 | 853.100710 | AFG | 4 |
| 3 | Afghanistan | Asia | 1967 | 34.020 | 11537966 | 836.197138 | AFG | 4 |
| 4 | Afghanistan | Asia | 1972 | 36.088 | 13079460 | 739.981106 | AFG | 4 |
Question 1:¶
Recreate the barplot below that shows the population of different continents for the year 2007.
Hints:
- Extract the 2007 year data from the dataframe. You have to process the data accordingly
- use plotly bar
- Add different colors for different continents
- Sort the order of the continent for the visualisation. Use axis layout setting
- Add text to each bar that represents the population
In [3]:
# YOUR CODE HERE
# Filter data for the year 2007
new_df = df[df['year'] == 2007].groupby("continent").sum().reset_index()
fig = px.bar(new_df,
x="pop",
y="continent",
labels={'pop': 'Population', 'continent': 'Continent'},
color="continent")
fig.show()
In [4]:
# YOUR CODE HERE
fig.update_yaxes(categoryorder='total ascending')
fig.show()
Question 3:¶
Add text to each bar that represents the population
In [5]:
# YOUR CODE HERE
fig.update_traces(texttemplate='%{x:.2s}', textposition='outside')
Question 4:¶
Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years
In [6]:
# YOUR CODE HERE
df_year_grouped = df.groupby(["year", "continent"]).agg({'pop': 'sum'}).reset_index().sort_values(by="year")
df_year_grouped = df_year_grouped.sort_values(by=["year", "pop"], ascending=[True, False])
fig_ani = px.bar(df_year_grouped,
x="pop",
y="continent",
labels={'pop': 'Population', 'continent': 'Continent'},
color="continent",
animation_frame="year",
animation_group="continent",
range_x=[0, 4000000000])
fig_ani.update_layout(yaxis={'categoryorder': 'total ascending'})
fig_ani.show()
Question 5:¶
Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years
In [11]:
# YOUR CODE HERE
#df_con = df[['year', 'country', 'pop']]
#df_con_grouped = df_con.groupby(["year", "country"]).agg({'pop': 'sum'}).reset_index()
#df_con_grouped = df_con_grouped.groupby('year', group_keys=False).apply(lambda x: x.sort_values('pop', ascending=False))
df_con = df.groupby(['year', 'country']).sum().reset_index()
fig_con = px.bar(df_con,
x="pop",
y="country",
labels={'pop': 'Population', 'continent': 'Continent'},
color="country",
animation_frame="year",
animation_group="country",
range_x=[0, 1500000000])
fig_con.update_layout(yaxis={'categoryorder': 'total ascending'})
fig_con.show()
Question 6:¶
Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation
In [12]:
# YOUR CODE HERE
fig_con.update_layout(height=1000)
In [14]:
# YOUR CODE HERE
df_top10 = df.groupby(['year', 'country']).sum().reset_index()
fig_new = px.bar(df_top10,
x="pop",
y="country",
labels={'pop': 'Population', 'continent': 'Continent'},
color="country",
animation_frame="year",
animation_group="country",
range_x=[0, 1500000000]
)
fig_new.update_layout(height=600)
fig_new.update_yaxes(range=(131.5, 141.5))
fig_new.update_layout(yaxis={'categoryorder': 'total ascending'})
fig_new.show()